1. What is this?

A high-level, very casual, and often self-deprecating look at trends in catches of Tyee salmon in Campbell River’s legendary Tyee Pool. All data exploration is being completed for fun and to learn some new tools (namely R Markdown and plotly).

There are far more technical ways of examining this data, but they aren’t as much fun - and are frankly hard. This analysis is living and will evolve over time. All results and interpretation are purely speculative and should be considered nothing more than ramblings of a fish nerd.

1.1 The data

This analysis uses the following publicly available data:

  1. Annual catch records from the Tyee Club.
  2. Discharge data collected on the Campbell River by the Water Survey of Canada.
  3. Annual Chinook Salmon escapement data available in the DFO NuSEDS database.
  4. Annual catch statistics from the North Pacific Anadromous Fish Commission
  5. Area based commercial catch statistics from DFO are available from 2001 to 2016
  6. Straight of Georgia herring spawn and catch data

This is certainly an interesting dataset, especially given it is the Tyee Club centenary, but it has its limitations. For example, there is no information on effort (# boats per day) and biological data is limited (e.g. size, girth and age of tyees or number of undersized fish captured).

2. Chinook Salmon

2.1 What we* know about Campbell River Chinook?

(* more like what have other learned about Campbell River Chinook Salmon, I don’t know much).

There has been a lot of information collected on Campbell River Chinook Salmon, including from Tyee Salmon captured in the Tyee Pool, however, most of this data is not readily available online. Data that is available (and that I have found) is summarized below.

2.1.1 Spawn Timing

  • Chinook spawning occurs from late September through early November and peaks in mid-October and that spawners reside in the river for ~12 days.

2.1.2 Age Class Structure

  • A roughly equal proportion of spawners return to the Campbell River as age-4 and age-5 fish (see Table 1) Sturham et al. 1999.

  • However, Ewart & Anderson,2013 report that Age-5 fish were dominant in 2012 (61%), with Age-4’s accounting for only 37% of the run, and age-3’s representing only 2%.

2.1.3 Size-at-Age

  • I have not found any measures of individual fish. But binned data from Sturham et al. 1999 shows that Age-4 fish generally range in size from 550-949 mm (mean ~ 780 mm) and age-5 fish range from 700-949 mm (mean ~ 840 mm). Age-6 fish were identified, but accounted for less than 1% of all fish in the Campbell (n = 1 fish, 930 mm) and Quinsam rivers

2.1.4 Fecundity

  • Ewart & Anderson, 2013 report that female Chinook in the Campbell River in 2012 carried roughly ~5,700, a decrease from the roughly 6,000 eggs typically carried.

2.1.5 Juvenile Life History

  • Juvenile Chinook Salmon in the Campbell River have been studied intensively since 2015 (e.g. Thornton et al. 2022. These data suggests fry emerge in February-March and that nearly all Campbell River Chinook out migrate as Age-0+ juveniles from March through July. Smaller recently emerged Age-0+ fry are dominant and typically captured from March through early May (37 to 52 m). Larger Age-0+ smolts are less common and move out from May through July (64 to 88 mm).

2.1.6 Estimated Juvenile Production

  • Estimates of juvenile Chinook production based on numbers of observed spawners have generally been less than numbers trapped throughout the outmigration period (Thornton et al. 2022, which may be due to increased juvenile survival or inaccurate/coarse estimates of fecundity.

2.1.7 Estimates of Marine Survival

  • Marine survival of unfed fry released from the Quinsam hatchery range from 0.2% to 0.4% (yes, that is less than 1%) (Ewart & Anderson 2013).

2.1.8 Hatchery Influence and Population Status

  • Ewart & Anderson 2013 report that 56% of the otoliths examined from the 2012 return showed no signs of hatchery marking and are assumed wild. The remaining 44% are presumed to have originated from instream incubators (31%), seapen released smolts (4%) and Quinsam River released smolts (9%).
Table 1. Size at age of Chinook Salmon captured in Campbell River watershed from Sturham et al. 1999
Waterbody Age n % of Total Size Range
(mm)		 Mean Lenght
(mm)
Campbell River 3 6 7.9 500 - 699 595.0
Campbell River 4 34 44.7 550 - 949 779.5
Campbell River 5 35 46.1 700 - 949 842.5
Campbell River 6 1 1.3 900 - 949 930.0
Quinsam Hatchery 3 76 20.2 400 - 749 619.5
Quinsam Hatchery 4 225 59.8 550 - 899 743.5
Quinsam Hatchery 5 73 19.4 700 - 949 834.0
Quinsam Hatchery 6 2 0.5 750 - 849 784.0
Quinsam River 3 46 22.8 500 - 849 663.0
Quinsam River 4 114 56.4 550 - 949 733.5
Quinsam River 5 40 19.8 700 - 949 818.0
Quinsam River 6 2 1.0 800 - 849 838.0

3. Let’s look at the Tyee catch data!

So, let’s begin by having a look at the catch data from the Tyee pool and seeing how catches fluctuate relative to Chinook Salmon escapement in the Campbell River.

Figure 1: Trends in Tyee Salmon captures and Campbell River Chinook Salmon escapement.

A quick look at Tyee catches (blue vertical bars) in Figure 1 shows:

  1. There is a fairly clear 4-year cycle of relatively higher catches (highlighted with shading). Which is interesting, and raises lots of questions…
  2. There has been a consistent decline in the number of Tyee salmon captured per year.
  3. There was a major crash or failure in 2014.

If we look at Escapement data (blue line) shown in Figure 1 , we can see:

  1. There has been a general declining trend in escapement (consistent with regional trends),
  2. Periods of increased escapement correspond with periods of increased Tyee catches, but not always (e.g. 2005, 2017 and 2020). Given the lack of information on effort (e.g. # of boats fishing per day) we cannot tease apart whether the lack of catches in some years is due to reduction in pressure.
  3. It is also possible that years with high escapement and low Tyee numbers were due to an increased proportion of smaller fish returning to the Campbell. Without annual information on age structure I cannot tease this apart.

Now, lets see when fish are most frequently captured throughout the season, and if there has been a change over time.

Figure 2: Total fish captured by date and decade

HEY! Who let someone register a Tyee in the first week of July!? This plot will become a lot more interesting once I can get my hands on some historical data.

3.1. What could be affecting returns and catches?

At it’s most basic level, there are four things that are likely affecting catches of Tyee salmon (in reality, there are many many many many many more.

3.1.1. Juvenile recruitment

  • This is determined by the number of eggs that are deposited (for easy math, lets say females account for 50% of escapement, that each one deposits 4000 eggs and that egg to fry survival is 10%). We will assume that fish that survive to fry will enter the sea. Hydrometric data on the Campbell is available back to 1949 and it is likely that extreme high or low flow events (e.g. greater than 300 cms, less than ??50 cms??) during the incubation/rearing periods (maybe November through March) will reduce juvenile recruitment.

3.1.2. Marine survival and productivity

  • This is way too complicated for right now. Let’s feel warm and fuzzy by assuming survival and productivity are stable (side note, they arent!). But if we don’t do this we can’t assume that proportions calculated from Sturham et al. are representative of current returns (unfortunately recent evidence shows this assumption is wrong and that fish are decreasing in size, so there are likely fewer Tyee returning now than in previous years).

3.1.3. Fishing effort and catchability

  • For now, I am going to assume effort (# of boats fishing per tide/day) is constant and that catchability (percent of Tyees present that are captured) are stable. In reality, effort has likely decreased over time (especially since 2014) and catchability has likely increased as peoples knowledge, skill and fishing technology have improved over time (not everyone though, I still suck). Either way, without some hard data it is hard to much with this.

3.1.4. Fishing Conditions

  • No question that fewer fish will be captured during seasons with poor fishing conditions (e.g. very windy, lots of rain). It is also possible that fish behaviour will change in response to river conditions. Certainly there was a lot of speculation that high flows during the 2022 Tyee season contributed to record low catches.

4. So, what can we look at?

Off the top of my head there are two ways we can approach this:

1.) We can look at what factors influenced how many fish were available for capture in the Tyee pool (i.e. how historic conditions may have contributed to observed captures), and/or;

2.) We can look at what factors influenced how returning fish were captured (i.e. conditions during the fishing season)

4.1 How Historic Conditions Influenced Captures

We can VERY CRUDELY estimate the number of salmon that should return to the Campbell River if we make a couple of big assumptions:

  • Fecundity is ~5,700 eggs per female (Ewart & Anderson, 2013

  • Sex ratios are 60:40 female to male using Sturham et al. 1999) data for Campbell River)

  • Egg-to-fry survival is approximately 0.1, can’t recall where this number came from but its commonly used as a measure of egg-to-fry survival of wild fish (compared to 0.9 for hatchery reared fish). Give results from Thornton et al. 2022 it is likely that egg-to-fry survival in the Campbell is higher.

  • Marine survival (smolt to adult) is approximately 0.003 (Ewart & Anderson, 2013

  • 7.9% of fish will return as Age-3, 44.7% of fish will return as Age-4 fish, 46.1% will return as Age-5 fish and 1.3% will return as Age-6 fish.

We can expand this to estimate the number of Tyee salmon that will return if we make even more assumptions!

  • For fun, let’s assume all fish > 900 mm are Tyee Salmon (I know girth is important too, but I dont have girth data) and using the Sturham et al. 1999) data as a rough guide I will assume that 10% of Age-4 male adults are >900 mm, 15% of Age-5 fish (males and females) are >900 mm and 85% of Age-6 fish are >900 mm.

If we run these numbers, each female will generate 1.7 offspring, of which 0.14 will be Age-3, 0.76 will be Age-4, 0.79 will be Age-5 and 0.022 will be Age-6. Furthermore, each female will produce 0.32 Tyee salmon. Let’s take a moment to remember that these assumptions are terrible. Larger fish are more likely to produce larger fish, so in reality some fish will produce a decent number of Tyee and others will produce none. But let’s keep it simple for now and assume every fish is able to make an equal number of Tyees

Based on this, each female should produce 1.71 offspring that return to spawn. Which is less than ideal.

Figure 3: Predicted returns by age-class relative to measured escapement, assuming 10% egg to fry survival.

Well that’s interesting. There are periods when my predicted returns closely align with actual escapement (most closely from 2003 to 2007, but my values are comparable from 2003 to 2010). This suggests my estimates may not be WAY off but does not confirm they are correct. Other notes:

  • Also clearly periods when my predictions are off! Most notably from 1998 to 2002, 2011-2012, 2014 and 2019 to 2022.
  • There are number of years where something appears to have happened and fish simply did not return (2005, 2011, 2014).
  • There are also years where something positive appears to have happened and far more fish than expected returned to the river (1999 to 2001, 2020).

How does this change if we increase egg-to-fry survival to 0.2?

I wonder how my predicted tyee returns align with actual tyee captures.

Figure 4: Comparison of catches of Tyee Salmon, predicted returns of Tyee Salmon and annual Chinook Salmon escapement counts.

Well, even though my estimates are clearly wrong, this is still interesting. There is a fairly drastic shift in predicted returns that coincides with the crash in 2014. Prior to the crash, predicted returns are consistently underestimated (73% of years are less than actual catches) whereas after the crash predicted Tyee returns are greater than total tyee catches in all but one year. Not sure exactly what this means, or how to interpret it, but I think its worth considering:

  • Only a proportion of all returning Tyees are captured each year. If all Tyee salmon were captured each year, we would be actively selecting against large fish and it would be reasonable to expect to see a continuous decline in the total number of Tyees returning each year. So, based on this logic (and my personal observation of tyees on the spawning ground), the predicted Tyee returns should always be greater than total catches.
  • The formula and values used to estimate predicted returns of tyee salmon do not change. If we assume there is no change in catchability and that the number of Tyees captured in the pool is a representation of the actual number of Tyee salmon that return to the river there appears to have been a dramatic reduction in the number or proportion of Tyee salmon in 2014. Given low escapement in 2014, it is most likely a poor return rather than a reduced proportion of Tyee.
  • Additionally, the figure shows that my formula and estimates are way off - which is not surprising as they were very crude! This is most apparent in the years prior to the 2014 crash, but suggests predictions after the crash are also off too.

So, what happened in 2014!? Did runs crash everywhere? Let’s have a look at escapement in other systems in the area.

Figure 5: Chinook Salmon escapement from rivers on East and West Coast of Vancouver Island.

Well, that figure sucks. But it shows how variable escapement is between years. On the East Coast of the Island, abundance increased in ’r format(3/7*100, digits = 2)`% of plotted streams and decreased in all others. Decreases

Relative to 2013, abundance in all plotted west coast streams was slightly reduced in 2014. There was a major crash in the Burnam River, but this is exaggerated by unusually high returns in 2013, 2015 and 2016.

MAYBE RERUN ESCAPEMENT PLOT USING ALL ESCPAEMENT DATA!? FACET BY AREA?

ADD METRIC THAT STANDARDIZES ESCAPEMENT. E.G. total annual returns vs mean annual returns.

Influence of river flow on catches

Last year there was a lot of speculation that high flows in the Campbell River may have caused fish to move directly into the river rather than staging in the pool. Let’s look at flow in the Campbell River to see how 2022 flows compared to previous years.

Figure 6: Catches of Tyee Salmon since 2016 relative to flow in the Campebll River.

Well, it’s clear that flows in 2022 were higher than past years and higher than mean flows over the past 5-years. But this doesn’t mean that is why fewer fish were captured. Either way let’s take a closer look at the correlation between flow and capture.

## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'

Figure 7: Relationship between river flow and fish capture

Figure 7 shows a strong negative relationship between discharge and the number of fish that are captured. This is what you would expect, that fish will hold in the pool while flows are low and that they will move into the river when flows are higher and they can safely navigate upstream. However, the fishery occurs during the late summer, when flows are typically low and it is possible that the timing of the fishery has contributed to observed trends.

OK, well there is a relationship (that could be due to a number of things). Lets have a look at some of the older data.

Figure 8: Catches of Tyee Salmon since 2007 relative to flow in the Campebll River.

Let’s look at commercial catches. Maybe there is a fishery that could be intercepting a large number of Tyees.

can.catch <- comm.catch %>% rename(Catch.Type = 'Catch Type',
                                   Data.Type  = 'Data Type') %>%
                            mutate(Area         = as.factor(Area),
                                   Species      = as.factor(Species),
                                   Year         = as.numeric(Year),
                                   Catch.Type = as.factor(Catch.Type)) %>%
                            filter(Country   ==  "Canada",
                                   Year      >= 1997,
                                   Data.Type == "Number (000's)")

can.catch.cn <- can.catch %>% filter(Species   == "Chinook",
                                     Area      == "Whole country")

      CN.catch.plot <- ggplot(can.catch.cn) +
                              geom_line(aes(x = Year, y = Total.Catch, color = Catch.Type)) +
                       labs(x = "Year", y = "Total Catch (0000's of fish") +
                       theme_bw()
      
      CN.catch.plot

can.catch.cn2 <- can.catch %>% filter(Species   == "Chinook",
                                      Catch.Type == "Sport")
      summary(can.catch.cn2)
##    Country          Whole Country/Province/State
##  Length:125         Length:125                  
##  Class :character   Class :character            
##  Mode  :character   Mode  :character            
##                                                 
##                                                 
##                                                 
##                                                 
##                           Area       Species          Catch.Type 
##  Haida Gwaii                :25   Chinook:125   Commercial :  0  
##  North Coast                :25   Cherry :  0   Sport      :125  
##  South Coast                :25   Chum   :  0   Subsistence:  0  
##  West Coast Vancouver Island:25   Coho   :  0                    
##  Whole country              :25   Pink   :  0                    
##  Amur River Basin           : 0   Sockeye:  0                    
##  (Other)                    : 0   (Other):  0                    
##   Data.Type              Year       Total.Catch    
##  Length:125         Min.   :1997   Min.   :  0.00  
##  Class :character   1st Qu.:2003   1st Qu.: 25.80  
##  Mode  :character   Median :2009   Median : 54.00  
##                     Mean   :2009   Mean   : 77.34  
##                     3rd Qu.:2015   3rd Qu.: 92.49  
##                     Max.   :2021   Max.   :306.68  
## 
      CN.catch.plot2 <- ggplot(can.catch.cn2) +
                              geom_line(aes(x = Year, y = Total.Catch, color = Area)) +
                                   labs(x = "Year", y = "Total Catch (0000's of fish") +
                                   theme_bw()
      CN.catch.plot2

can.catch.sk <- can.catch %>% filter(Species   == "Sockeye")

colnames
## function (x, do.NULL = TRUE, prefix = "col") 
## {
##     if (is.data.frame(x) && do.NULL) 
##         return(names(x))
##     dn <- dimnames(x)
##     if (!is.null(dn[[2L]])) 
##         dn[[2L]]
##     else {
##         nc <- NCOL(x)
##         if (do.NULL) 
##             NULL
##         else if (nc > 0L) 
##             paste0(prefix, seq_len(nc))
##         else character()
##     }
## }
## <bytecode: 0x000002accbe05d30>
## <environment: namespace:base>
summary(can.catch.cn2)
##    Country          Whole Country/Province/State
##  Length:125         Length:125                  
##  Class :character   Class :character            
##  Mode  :character   Mode  :character            
##                                                 
##                                                 
##                                                 
##                                                 
##                           Area       Species          Catch.Type 
##  Haida Gwaii                :25   Chinook:125   Commercial :  0  
##  North Coast                :25   Cherry :  0   Sport      :125  
##  South Coast                :25   Chum   :  0   Subsistence:  0  
##  West Coast Vancouver Island:25   Coho   :  0                    
##  Whole country              :25   Pink   :  0                    
##  Amur River Basin           : 0   Sockeye:  0                    
##  (Other)                    : 0   (Other):  0                    
##   Data.Type              Year       Total.Catch    
##  Length:125         Min.   :1997   Min.   :  0.00  
##  Class :character   1st Qu.:2003   1st Qu.: 25.80  
##  Mode  :character   Median :2009   Median : 54.00  
##                     Mean   :2009   Mean   : 77.34  
##                     3rd Qu.:2015   3rd Qu.: 92.49  
##                     Max.   :2021   Max.   :306.68  
## 
CN.catch.plot

sk.catch.plot <- ggplot(can.catch.sk) +
                        geom_line(aes(x = Year, y = Total.Catch, color = Species, linetype = Catch.Type))
sk.catch.plot

###Notes Plot peak flows 4 to 5 years previous (e.g. impact of peak flows on recruitment). - Assume mortality at >200 cms - spawning habitat lost at 300-400 cms - Is Quinsam flow regulated? Ask Mary.

Is return age genetic? Or environmental?

Supplemental Tables and Figures

Table 1. Size at age of male and female Chinook Salmon captured in Campbell River watershed
Waterbody Sex Age n % of Total
(by Sex)		 % of Total
(by Stream)		 Size Range
(mm)		 Mean Lenght
(mm)		 Std. Error
Campbell River F 3 0 0.00 0.00 500 - 699 595 20.82
Campbell River M 3 6 0.19 0.08 500 - 699 595 20.82
Campbell River F 4 21 0.48 0.28 700 - 899 783 10.69
Campbell River M 4 13 0.41 0.17 550 - 949 776 23.30
Campbell River F 5 23 0.52 0.30 750 - 949 839 7.51
Campbell River M 5 12 0.38 0.16 700 - 949 846 14.43
Campbell River F 6 0 0.00 0.00 900 - 949 930 0.00
Campbell River M 6 1 0.03 0.01 900 - 949 930 0.00
Quinsam Hatchery F 3 9 0.04 0.02 550 - 749 644 15.33
Quinsam Hatchery M 3 67 0.38 0.18 400 - 749 595 6.84
Quinsam Hatchery F 4 130 0.65 0.35 600 - 899 742 3.77
Quinsam Hatchery M 4 95 0.54 0.25 550 - 899 745 5.64
Quinsam Hatchery F 5 61 0.30 0.16 700 - 949 823 5.76
Quinsam Hatchery M 5 12 0.07 0.03 750 - 949 845 13.57
Quinsam Hatchery F 6 1 0.00 0.00 800 - 849 812 0.00
Quinsam Hatchery M 6 1 0.01 0.00 750 - 799 756 0.00
Quinsam River F 3 1 0.01 0.00 700 - 749 700 0.00
Quinsam River M 3 45 0.41 0.22 500 - 849 626 12.07
Quinsam River F 4 58 0.63 0.29 650 - 849 744 4.73
Quinsam River M 4 56 0.51 0.28 550 - 949 723 9.35
Quinsam River F 5 31 0.34 0.15 700 - 949 830 7.54
Quinsam River M 5 9 0.08 0.04 700 - 949 806 21.00
Quinsam River F 6 2 0.02 0.01 800 - 849 838 2.83
Quinsam River M 6 0 0.00 0.00 800 - 849 838 2.83